It is well established that motor vehicles carrying multiple passengers reduces fuel consumption, highway congestion, pollution, and the like. Highway authorities provide incentives for high occupancy vehicles which include allowing such vehicles to travel in restricted traffic lanes. Penalties are imposed on drivers of vehicles travelling with less than a defined number of occupants (e.g., less than 2). Efforts have been directed towards image capture systems and methods to effectuate HOV lane enforcement. Manual enforcement of HOV/HOT lanes by law enforcement can be difficult and potentially hazardous. Pulling violating motorists over to issue tickets tends to disrupt traffic and can become a safety hazard for both the officer and the vehicle's occupants. Consequently, occupancy detection systems which automatically detect the number of human occupants in a motor vehicle are desirable. Development is ongoing as methods are needed to analyze images captured of moving motor vehicles to determine the number of occupants in that vehicle.
To detect human occupants in the visible wavelength range, intrinsic properties, such as shape, color, and features such as, for example, head shape, eyes, etc., have been utilized. However, these properties are affected by extrinsic factors such as illumination spectrum, illumination variation, similarities of shape and texture, and the like. Active near-infrared (NIR) illumination has been applied to address those extrinsic effects but better performance is still desired in practical applications due to the similarity in reflectance of human skin and other materials, reflected light from windows, stray light from the environment, weather conditions, etc. Since NIR wavelengths are in the CCD range, cameras are available at relatively low cost. However, for imaging through windshields, NIR wavelengths are not very effective. Present single-band infrared cameras use 2D imaging in the NIR wavelength range with a CCD detector array. Whereas, many multiband infrared camera systems use the short wave infrared (SWIR) band by imaging on, for instance, an InGaAs detector array with multiple filters. These systems exploit the physical geometries and material properties at different optical wavelengths in the infrared band. However, such systems lack the ability to capture depth information for 3D image reconstruction. Acquiring a 3D image of a vehicle's occupants increases the accuracy of occupancy determination and thus overall system performance.
Accordingly, what is needed in this art are increasingly sophisticated systems and methods which combine a structured illumination source in the short wave infrared (SWIR) wavelength range with the detection capabilities of near infrared (NIR) devices to generate a 3D image of a motor vehicle traveling in a HOV/HOT lane for accurate determination of the number of occupants in that vehicle.